System and method for assessment of cardiac stroke volume and volume responsiveness

ABSTRACT

Disclosed are systems and methods using ultrasound to predict if a patient&#39;s cardiac stroke volume will increase with a fluid bolus. Ultrasound measures are taken before administering a fluid bolus, including measurement of the left ventricular outflow tract velocity time integral (LVOT VTI), and venous measurements of the internal jugular vein. Data collected from such ultrasound scan is then used to predict the patient&#39;s cardiac volume response in the event that a fluid bolus is administered to that patient.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based upon and claims the benefit of U.S.Provisional Patent Application Ser. No. 62/278,717 entitled “CombinationAssessment of Volume Status (CAVS),” filed with the U.S. Patent andTrademark Office on Jan. 14, 2016 by the inventor herein, and of U.S.Provisional Patent Application Ser. No. 62/443,276 entitled “Method forEstimation of Cardiac Stroke Volume (eSV) and Cardiac Output (eCO),”filed with the U.S. Patent and Trademark Office on Jan. 6, 2017, thespecifications of which are incorporated herein by reference in theirentireties.

STATEMENT OF GOVERNMENT SUPPORT

This invention was made with government support under Grant No.FA8650-13-2-6D10 awarded by the Air Force Office of Scientific Research.The Government has certain rights in the invention.

FIELD OF THE INVENTION

The present invention relates generally to clinical medical treatment ofcritically ill patients, and more particularly to systems and methodsfor assessing cardiac stroke volume in a patient, and to methods forpredicting a patient's stroke volume response to a fluid bolus.

BACKGROUND OF THE INVENTION

Early and aggressive fluid resuscitation in patients suffering fromshock is associated with improvement in outcome, including mortality.Multiple studies have supported this concept in a variety of clinicalsettings, from septic shock to high-risk surgical patients. However, aclear association also exists between cumulative fluid balance andmortality. It therefore becomes prudent to adopt a tailored approach tofluid resuscitation over empiric fluid loading. After all, a fluid bolusthat does not lead to increased stroke volume is unlikely to benefit thepatient, and carries all of the risk associated with volume overload.

Multiple methods, invasive or otherwise, have been proposed to predictan increase in cardiac stroke volume (referred to herein at times as SV)with a fluid bolus, or which increase in stroke volume is referred to asvolume responsiveness (referred to herein at times as VR). Stroke volume(measured in ml/beat) is the amount of blood pumped out of the heartwith each beat (and more specifically a cone of blood that comes throughthe left ventricular outflow tract (LVOT)). Stroke volume is also animportant determinant of fluid status, and thus can be helpful indirecting the administration of fluid boluses. While central venouspressure (CVP) has traditionally been used to assess volume status,studies have not demonstrated a reliable relationship between CVP andvolume responsiveness. Pulmonary artery catheters (PAC) have also fallenout of favor due to their invasiveness and potential for seriouscomplications. Several studies have failed to show any improvement inoutcome associated with PAC use. Given its non-invasive nature,portability, and ease of use as a point-of-care test, ultrasound (US)has emerged as an attractive option to assess volume status and predictfluid responsiveness.

The most studied ultrasound measure is respiratory variation in theinferior vena cava (rvIVC). This measure is relatively easy to performwith any point-of-care ultrasound system. While multiple studies havedemonstrated that rvIVC accurately predicts volume responsiveness inmechanically ventilated patients, there is conflicting evidence inspontaneously breathing patients. rvIVC measurement may be difficult orimpossible to perform in many surgical patients, and particularly thosepresenting with abdominal distension, surgical wounds, morbid obesity,or bowel gas. Additionally, evidence suggests that in the setting ofincreased thoracic and abdominal pressures, IVC diameter andcollapsibility indices may lose their reliability.

Given the varied and limited successes of prior known methods, whichgenerally assess only one metric, it would be advantageous to providemore easily implemented system that allows several ultrasound metrics tobe included in the measurements and predictions. This would allowhealthcare providers to administer fluid only to those patients mostlikely to have a positive response, who have a low stroke volume tobegin with and limiting application to those least likely to have apositive response (and thereby reducing the risk of volume overload insuch patients). It would also be advantageous to provide systems andmethods of using noninvasive ultrasound measurements to predict whethera given patient will be likely to have a positive volume response to afluid bolus prior to its administration.

SUMMARY OF THE INVENTION

Disclosed herein are systems and methods for using ultrasound to predictvolume responsiveness in critically ill surgical patients and thosesuffering from shock. In accordance with certain aspects of anembodiment of the invention, computer software applications are providedthat support point-of-care ultrasound (POCUS) that perform one or moreof (i) allowing physicians to more easily and accurately predict whichpatients will benefit from a fluid bolus, and (ii) simplifying andstandardizing the measurement of stroke volume and cardiac output. Suchsoftware applications may include an interactive calculator useful forguiding fluid administration, use of vasopressors, and use of inotropicmedications. Such computer software may be helpful in supportingclinical decision making, which the field has thus far seen little of byway of software application development. More particularly, to theknowledge of the inventor, there are no known currently availableapplications that allow for the POCUS-driven hemodynamic analysisdiscussed herein, and none of the known software packages offered onavailable ultrasound systems have the performance capabilities disclosedherein.

The systems and methods set forth herein allow for POCUS to be performedand interpreted by a healthcare provider, such as a treating physician,sonographer, echocardiologist, or radiologist, when evaluating patientvolume responsiveness, allowing the healthcare provider to make relatedmedical decisions based on test results faster than by a standard methodof operation. When using a standard US system the healthcare providerorders an exam, the patient then goes to a different site, the US isperformed by a sonographer, the results are interpreted by acardiologist or radiologist, and a written report is generated and sentback to the treating physician.

The software operable with such prior known US systems is designed forthis standard method of operation. That method is complex, cumbersomeand does not provide data in a format designed to guide real-timeclinical decision-making. Despite these challenges, the desire isgrowing to apply POCUS across a wide variety of aspects of medicine.

For instance, POCUS can be used anywhere, from outer space in theinternational space station to the remote corners of Brazil and Africa.The modality itself is rapid, safe, portable, and far less expensivethan other imaging technology, such as CT. However, healthcare providershaving minimal training with POCUS are using the system to makeimportant decisions despite using US systems created for a differenttype of healthcare provider.

In accordance with certain aspects of the invention, methods, includingcomputer-implemented methods, are provided that allow healthcareproviders to more easily and accurately measure SV and to predict if thepatient is likely to have a positive response to a fluid bolus, suchthat there is a likelihood that the patient's SV will increase with afluid bolus. Such method was derived from a volume responsiveness study(discussed in detail below) that comprised an observational study of 138patients receiving a fluid bolus. An echocardiogram was performed beforeand after the bolus, and patients who responded with an increase in SVwere identified (+VR). Several ultrasound measures were taken beforeadministering the fluid bolus, including an arterial measurementreferred to as the left ventricular outflow tract velocity time integral(LVOT VTI) and venous measurements of the internal jugular vein.

Computer modeling was then used to determine the most predicativecombination of variables, and the analytical and decision processesdescribed herein were created using those variables. Both the patient'sVTI and the patient's respiratory variation of the internal jugular werefound to be particularly predictive, and their combined assessment evenmore so, of a patient's volume responsiveness. The training receiveroperating curve (ROC) for accurately predicting+VR was excellent at 0.90(p<0.0001). Importantly, the model performed well with validationtesting, maintaining an ROC of 0.77 (p<0.0001).

In accordance with further aspects of the invention, methods, includingcomputer-implemented methods, are provided that streamline and simplifythe way in which SV itself is assessed by estimating left ventricularoutflow track diameter (eLVOTD) using patient characteristics includingage, sex, height, weight, and body surface area. Left ventricularoutflow tract diameter (LVOTD) is a determinant of stroke volume,discussed above, and of cardiac output (CO measured in L/min), both ofwhich are typically derived by echocardiography (ultrasound of theheart). CO is the stroke volume (measured in mL/beat) multiplied by theheart rate (HR measured in beats/min), and as with stroke volume, is avaluable measure of cardiac function, and thus can help determine theneed for inotropic support of the heart, especially if used with anotherechocardiographic measure. Also, in combination, mean arterial bloodpressure (MAP measured in mmHg) and CO can be used to determine thesystemic vascular resistance (SVR measured in dynes/cm²), which maydirect vasopressor use.

Stroke volume can be estimated using both the LVOTD and LV VTI. Whilethe VTI has been found to be reliably assessed by ultrasound in morethan 85% of patients, the inventor's clinical experience has shown thatLVOTD can be very difficult to accurately measure. More particularly,preliminary data has indicated that reliable ultrasound images fordetermining LVOTD are only present in about 50% of the data reviewed. Asa result, most POCUS cardiac evaluations are limited to simplequalitative assessments, including right ventricular function and leftventricular ejection fraction. Current state of the art for takingmeasurements of SV, CO, and SVR require an invasive hemodynamic monitorand a hospitalized setting.

In contrast, POCUS can be performed anywhere and is relatively riskfree. Initial modeling using the methods set forth herein showsreasonable agreement between eLVOTD and measured LVOTD, with an RMSE of0.15 and the R² of 0.74. Through use of the eLVOTD as discussed herein,SV and CO may be more easily and reliably assessed with POCUS. When suchquantitative echocardiogram data is combined with qualitative RV and LVEF assessment, POCUS will provide a better hemodynamic assessment toolthan currently exists.

BRIEF DESCRIPTION OF THE DRAWINGS

The numerous advantages of the present invention may be betterunderstood by those skilled in the art by reference to the accompanyingfigures in which:

FIG. 1 is a chart summarizing each of the ultrasound measures of volumeresponsiveness considered as having potential value as a predictor ofvolume responsiveness;

FIG. 2 is a chart reflecting values of each potentially predictivemeasure that is able to predict +VR or −VR in the measurable percentageof patients, including a negative predictive value and a positivepredictive value;

FIG. 3A is a graph illustrating pre-bolus VTI alone as a predictivemeasure of volume responsiveness;

FIG. 3B is a graph illustrating rv IJ as a predictive measure of volumeresponsiveness;

FIG. 4A is a pair of images showing scans of a patient's internaljugular vein taken when the patient was lying flat (0°) and sittingupright (90°) in a patient that did not respond to a fluid bolus, asshown by no change in the diameter of the internal jugular;

FIG. 4B is a pair of images showing scans of a patient's internaljugular vein taken when the patient was lying flat (0°) and sittingupright (90°) in a patient that did respond to a fluid bolus, as shownby a significant decrease in the diameter of the internal jugular;

FIG. 5 is a graph illustrating combination assessment of volume statusas a predictive measure of volume responsiveness;

FIG. 6 is a graph illustrating combination assessment of volume statusas a predictive measure of volume responsiveness in mechanicallyventilated patients; and

FIG. 7 illustrates one embodiment in accordance with the methoddescribed herein of combining several of the metrics as described toincrease the AUROC to 0.90.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The invention summarized above may be better understood by referring tothe following description, claims, and accompanying drawings. Thisdescription of an embodiment, set out below to enable one to practice animplementation of the invention, is not intended to limit the preferredembodiment, but to serve as a particular example thereof. Those skilledin the art should appreciate that they may readily use the conceptionand specific embodiments disclosed as a basis for modifying or designingother methods and systems for carrying out the same purposes of thepresent invention. Those skilled in the art should also realize thatsuch equivalent assemblies do not depart from the spirit and scope ofthe invention in its broadest form. Further, it should be understoodthat the figures are not drawn to scale and in some instances detailsthat are not necessary for the understanding of the present inventionare omitted such as common methods of manufacturing.

In accordance with certain aspects of an embodiment of the invention,methods, including computer-implemented methods, are provided that allowhealthcare providers to more easily and accurately predict if apatient's cardiac stroke volume will increase with a fluid bolus.According to one embodiment of the present invention, predicting thestroke volume responsiveness of a patient to a fluid bolus includesmeasuring the patient's respiratory variation of the internal jugular(rvIJ) and the patient's velocity time integral (VTI). A method andsystem, described below as combined assessment of volume status (CAVS),increases the accuracy of a healthcare provider's measurements andreduces the likelihood of risk to the patient.

To determine predicative factors capable of making such a prediction,patients admitted to an intensive care unit and receiving a fluid bolusor blood product transfusion for clinical indications were deemedeligible for enrollment in the study. After informed consent wasobtained, patients underwent two transthoracic echocardiograms (TTE);one just prior to the bolus/transfusion (pre-TTE), and a second upon itscompletion (post-TTE). The stroke volume was assessed in both exams, andthe percent change as a result of the fluid was calculated. Patientswith an increase of ≥15% in the stroke volume were determined to bevolume responsive (+VR). The predictive accuracy of several differentultrasonographic measures in assessing volume responsiveness weredirectly compared.

The relevant population was surveyed over a 36-month period,Monday-Friday from 7:00 a.m. to 4:00 p.m. Patients receivingcrystalloid, colloid or blood product transfusion were identified. Ifthe patient was able to consent, or the legally authorizedrepresentative of the patient was present, he or she was approached forenrollment. Administration of the fluid was not delayed for eitherenrollment or performance of the pre-TTE. Clinical data includingdemographic (age, sex, admission diagnosis) and clinical information(body surface area, mean arterial blood pressure, heart rate, 24 hourfluid balance) were extracted from the medical record. The ventilatorsettings and surgeries performed prior to the pre-TTE were recorded. Thetype and the type amount of the bolus was also noted.

All exams were performed by a dedicated cardiac sonographer or trainedsurgical intensivist using a Phillips CX-50® ultrasound system (Andover,Mass., USA) with a cardiac calculation package. For the cardiacmeasurements a phased array 3S cardiac transducer was used. For theinternal jugular (U) vein assessment a high frequency linear transducerwas employed. The pre-TIE was performed within thirty minutes of thefluid administration and the post within thirty minutes of itscompletion. Both exams were focused rapid echocardiographic exams (FREE)that includes four standard views: parasternal long axis (PLA),parasternal short axis (SA), apical (AP), and sub-xhvphiod (SX). FREE issimilar to a standard TTE, except that the measurements andinterpretation are hemodynamically rather than anatomically oriented.Ejection fraction and diastolic function is assessed as part of theFREE. The internal jugular measurements described below were added tothe pre-TTE as part of the analysis:

In both the pre- and post-TTE, the stroke volumes of a patient wasassessed using pulsed-wave Doppler US through the left ventricularoutflow tract (LVOT) from the AP window. The VII and the leftventricular outflow tract diameter in the PLA was measured to calculatethe patient's SV. If the patient was in atrial fibrillation, the averageof 5 beats was taken. The patient was excluded from the study if the SVmeasurements could not be obtained because either the patient's VTIcould not be measured due to anatomic reasons or aliasing was too highbecause of high velocity flow. The pre- and post-bolus VTI were recordedand the percent change in stroke volume was determined by the equation:Percent Change in SV=((Post VTI-Pre VTI)/Pre VTI))*100Respiratory variation in the inferior vena cava (rvIVC) was thenevaluated in M-mode. More particularly, the liver was identified from asub-costal view. The IVC was located in long axis passing into the rightatrium. A cursor was placed just proximal to the insertion of thehepatic veins, approximately 2 cm into the liver. M-mode was recordedover several respiratory cycles. The maximum and minimum diameter of theIVC was determined and recorded.

Similarly, the rvIVC was evaluated in 2D. As described above, the IVCwas located in long axis. Rather than looking at the hepatic veininsertion, the entire IVC was assessed to determine if the patient hadrespiratory variation anywhere along the IVC. The maximum and minimumIVC measurements were obtained using a caliper. The percent change ofIVC for both M-mode and 2D was determined quantitatively (as describedbelow) and by simple visual assessment (e.g., indicating a yes or nochange). The percent change of the IVC was determined by the differenceof the maximum and minimum IVC diameters divided by the maximum IVCdiameter.

Similar to the SV measurement, as described above, respiratory strokevolume variation (rSVV) was obtained from the AP window by using pulsedwave Doppler US. To determine the rSVV, the sweep speed was decreased tosample both the maximum and minimum VTI from one screen. The SVVmeasurements could not be performed if the patient was in atrialfibrillation (afib). The peak flow and minimum flow was determined andthe rSVV was calculated using the equation:rsVV=((max VTI−min VTI)/max VTI))*100

Next, SV was evaluated with passive leg raise, in which the UStransducer was placed at the apical window so that the VTI could bemeasured. The patient was supine (0 degrees), with their legs and headflat on the bed. Both of the patient's legs were raised from 45 degrees(45°) to an upright position of 90 degrees (90°), and the VTI was againrecorded. The difference in with the patient's legs raised to theupright position was calculated.

Next, internal jugular vein (IJ) diameter was measured using a highfrequency linear transducer. The left IJ was imaged in short and longaxis, first with the patient in the supine position (0°), and again withthe head of the patient's bed positioned in the upright position (i.e.,at 90° to the patient's legs). By adjusting the head of the patient'sbed, the patient's head was maintained in a neutral position whileimaging the left U. The short axis view was taken in the mid-neck. Forthe long axis view, the transducer grove was aimed towards the patient'shead. The maximum and minimum diameter of the patient's left IJ in thesupine position (IJ 0° max and IJ 0° min, respectively) were measuredfrom the short axis view, and the maximum and minimum diameter of thepatient's left IJ in the upright position (IJ 90° max and IJ 90° min,respectively) were measured from the short axis view. The resultingsupine and uptight respiratory variations (ry IJ 0° and ry IJ 90°,respectively) and the change in cross sectional area were determined.Respiratory variation of positional change in the IJ was then calculatedas follows:

Respiratory variation 0° (rv IJ 0°) ((IJ 0° max-IJ 0° min)/IJ 0° max) ×100 Respiratory variation 90° (rv IJ 90°) ((IJ 90° max-IJ 90° min)/IJ90° max) × 100 Positional IJ change (pΔIJ) ((IJ 0°-IJ 90°)/IJ 0°) × 100

Patients were separated into two groups based upon the abovemeasurements: +VR (i.e. patients having a >15% increase in stroke volumewith a fluid bolus) and −VR (i.e. patients not having a >15% increase instroke volume with a fluid bolus).

A receiver operating characteristic (ROC) was used to determinethreshold values for sensitivity and specificity. Standard ROC'sdetermine a single threshold value that detects the most accurate singlemeasurement. However. US is better understood as a semi-quantitive toolbecause estimates and ranges are generally more accurate forms ofmeasurements than absolute measurements for the healthcare provider touse. To create a more useful clinical tool, the criterion and coordinatevalues of the ROC data were used to create upper and lower thresholdvalues for the best sensitivity and specificity of each measurementbelow X the outcome is very unlikely, above Y the outcome is verylikely, and between X and Y the outcome is indeterminate). The number ofpatients that had an indeterminate outcome was quantified. Logisticregression analysis was used to determine the most predictivecombination of variables. The sensitivity and specificity of eachmeasure were calculated using the threshold values. These analysesallowed a comparison of ranges between different measures.

Descriptive statistics were employed using a median with lower quartileand upper quartile (LQ-UQ) for continuous variables, and a number orpercentage (%) for categorical variables. A probability of results beingdue to chance (P-value) of <0.05 was considered statisticallysignificant.

A preliminary analysis determined that passive leg raise stroke volumevariation could not be reliably measured and was not predictive of +VR.Differentiating stroke volume variation secondary to respiration fromstroke volume variation resulting from raising the legs to the uprightposition was very difficult. It was also very difficult to determinewhen to measure the waveform after the patient's legs were raised to theupright position because many of the patients had anatomic limitations(e.g., femur or pelvic fractures), and movement of the lower extremitiesfrequently caused the patients discomfort. As a result, the passive legraise SVV measure was considered less preferable for predicting strokevolume responsiveness than the other measures, which were provedfeasible. Upon completion, the IVC was assessed in 78% of patients, theSVV was assessed in 87% of patients, and the IJ was assessed in 90% ofpatients.

FIG. 1 is a chart summarizing each of the ultrasound measures of volumeresponsiveness considered as having potential value as a predictor ofvolume responsiveness. In FIG. 1, the left column provides anabbreviation of the particular measure, followed by the definition ofthat measure, what metric the measure is used to assess, the ultrasoundmode in which it is measured, and finally how difficult the measure isto perform. Likewise, FIG. 2 is a chart reflecting values of eachpotentially predictive measure that is able to predict +VR or −VR in the“% measurable” percentage of patients. In FIG. 2, the left columnprovides the metric, followed by threshold values for −VR and +VR, thepercent of patients in whom the metric could be measured, and thenegative and positive predictive values for each of the measures notedin the chart, namely, combination assessment of volume status (CANTS asdiscussed below), velocity time interval (VTI), variations in thediameter of the internal jugular (IJ) from a change in position,respiratory variation (rv IJ 90°) in the internal jugular, respiratoryvariation in stroke volume variation (rvSVV), and respiratory variationin the inferior vena cava (rvIVC). The threshold values for +VR define apositive fluid bolus responsiveness value range, and vary from metric tometric (some being equal to and greater than a particular value, andsome being equal to and less than a particular value). As set forth inthe chart of FIG. 2, the negative predictive value is the likelihoodthat a negative result will identify a patient who will not respond to afluid bolus with an increase in SV whereas the positive predictive valueis the likelihood that a positive result will correctly identify apatient who's SV does increase.

37% of the final population of patients were calculated as ±VR, and 63%of the final population of patients were calculated as −VR. Pre-bolusejection fraction and diastolic function were found to not have aneffect on VR. Of the measures, pre-bolus VTI (p<0.001) and IJ measures(rv IJ 0° and pΔIJ; p<0.001 and) were found to be most significantlypredictive of an increase in stroke volume with a fluid bolus.

A measure of pre-bolus stroke volume (pre-bolus VTI) was the single mostpredictive measure of volume responsiveness. The area under the ROC(AUROC) curve was 0.71 (95% CI 0.64-0.77). Examination of the ROC showedthe best threshold value is ≥22 cm to detect non-responders (i.e. −VR),and ≤18 cm to detect responsive patients (i.e. +VR). This allowedassessment in 78% of patients with a sensitivity of 75% and specificityof 70%, FIG. 3A shows a graph of pre-bolus VII as a predictive measureof volume responsiveness, and particularly the accuracy of the VTI aloneto predict VR. The AUROC shows sensitivity (y-axis) graphed againstspecificity (x-axis), demonstrating the accuracy of the measure todetermine both −VR and +VR.

Further, respiratory variation in the internal jugular with the patientin the upright position (patient's head positioned at 90° to their legs,i.e. rv IJ 90°) was likewise found to be a significantly predictivemeasure of volume responsiveness. However, the AUROC for this measurewas only 0.65 (95% CI 0.57-0.71). Examination of the ROC for rv IJ 90°showed the best threshold value is less than 12% change in diameter todetect non-responders (i.e. −VR), and at least 25% change in diameter todetect responders (i.e. ±VR). FIG. 3B shows rv IJ 90° as a predictivemeasure of volume responsiveness, and particularly the accuracy of rv IJ90° alone to predict VR.

Still further, positional variation of the internal jugular (0-90° IJ)also appeared to be a predictor of volume responsiveness, though with astill lower AUROC of 0.61 (95% CI 0.54-0.69). Examination of the ROC for0-90° IJ showed the best threshold value is at most 12% change indiameter to detect non-responders (i.e. −VR), and at least 40% change indiameter to detect responders (i.e. +VR). FIGS. 4A and 4B provide imagesof scans of patient's internal jugular vein. FIG. 4A shows a pair ofimages showing the internal jugular above the carotid artery of apatient, taken when the patient was in the supine position (0°) and theupright position (90°) in a patient that did not respond to a fluidbolus, reflected by no change in the diameter of the internal jugular.Likewise, FIG. 4B shows a pair of images of a patient's internal jugularabove the carotid artery taken when the patient was in the supineposition (0°) and in the upright position (90°) in a patient that didrespond to a fluid bolus, reflected by a significant decrease in thediameter of the internal jugular.

Importantly, when the rvIJ and the VTI were considered together,referred to at times herein as combined assessment of volume status(CAVS), the accuracy increased with a resultant AUROC of 0.76 (95% CI0.69-0.82). FIG. 5 shows CAVS as a predictive measure of volumeresponsiveness, and more particularly an increase in the AUROC when VTIand IJ are combined. Likewise, when only mechanically ventilatedpatients were considered, all of the measures were found to be moreaccurate. FIG. 6 shows CAVS as a predictive measure of volumeresponsiveness in mechanically ventilated patients. FIG. 7 demonstratesthe current method of combining several of the metrics as described. TheAUROC rises to 0.90 when this is done.

Based on the foregoing predictive measures of volume responsiveness, andmore particularly on the values of those factors that may be used toestimate the SV and CO and to predict +VR and −VR, computer softwareapplications, including applications executable on US devices, personalcomputers, laptops, tablets, mobile devices, or any other computingdevices may be provided that employ such values in analytical algorithmsto receive the relevant data from an ultrasound transducer, to use thevalues noted above to determine whether a given patient is predicted tobe +VR or −VR, and to provide output to a user of the software, such asthe treating healthcare provider, that indicates the resultantprediction.

In a particular configuration, such software may specifically instructthe healthcare provider to administer a fluid bolus if the software hasdetermined that the patient, based upon the collected ultrasound data,is predicted to be +VR. Likewise, in a particular configuration, suchdevices operating such software may automatically administer (such as byway of issuing a control signal to an intraveneous pump or other device)a fluid bolus to the patient, again if devices operating the softwarehas determined that the patient, based upon the collected ultrasounddata, is predicted to be +VR. The software receives as input pertinentdemographic data (e.g., patient age, sex, height, and weight), clinicaldata (e.g., heart rate, systolic and diastolic blood pressure, andmechanical ventilation), and echocardiographic information (leftventricular outflow tract, velocity time integral, and internal jugularvein diameter variation). In accordance with certain aspects of aparticular embodiment, such data may be automatically communicated fromthe ultrasound transducer to the software upon its collection, such as(by way of non-limiting example) through a wireless data connectionbetween the ultrasound transducer and a BLUETOOTH® or wireless networkcommunication module on the computing device, or other suchcommunication channel as may be readily apparent to those skilled in theart.

In accordance with further aspects of the invention, methods, includingcomputer-implemented methods, are provided that streamline and simplifythe way in which stroke volume itself is assessed by estimating leftventricular outflow track diameter (eLVOTD) using patientcharacteristics including age, sex, height, weight, and body surfacearea of the patient. This provides a far less invasive method ofdetermining a patient's cardiac output and stroke volume than currentlyimplemented methods (i.e. placement of a pulmonary artery catheter (PAC)in the patient's heart), and more particularly allows for an accurateand reproducible echocardiographic calculation of cardiac output andstroke volume.

In order to estimate a patient's LVOTD, given the five variables of age,sex, height, weight, and body surface area, a design matrix Φ isconstructed of N study cases byΦ=( (x ₁),φ(x ₂), . . . ,φ(x _(N)))^(T), where

${{\phi\left( x_{i} \right)} = {{k\left( {x,x_{i}} \right)} = {\exp\left( {- \frac{{{x - x_{i}}}^{2}}{2\sigma^{2}}} \right)}}},$namely a radial basis kernel function. The indice i is selected as asubset with 19 elements from the N cases. Let Y^(est) stand forestimated LVOT, and x stand for the input variable vector [age, trainsex, height, weight, BSA]. The variable y^(train) stands for a vector ofknown LVOT values from N study cases. The estimation of LVOT iscalculated byy ^(est)=β(A+βΦ ^(T)Φ)⁻¹Φ^(T) y ^(train))^(T)φ(x ^(new)),where β is the precision, A is a diagonal matrix which has its diagonalelements as ([1.8889, 1.2808, 0.2040, 0.9562, 0.7816, 1.4284, 1.8667,0.4921, 0.4915, 1.4424, −0.4183, 1.5402, −2.2315, 1.7672, 0.6347,0.9039, 0.6460, 1.2622, 1.3778]), and all other elements are zeros.

Through such estimation of the patient's LVOT, the healthcare providerusing a device operating the software employing the foregoing method mayinput clinical and echocardiographic data and be able to deriveimportant hemodynamic information, including cardiac output and strokevolume. According to some aspects, cardiac output is used in conjunctionwith the mean arterial blood pressure to calculate the systemic vascularresistance, and stroke volume is the most important measure of apatient's responsiveness of volume status, such as the patient'sresponsiveness to a fluid bolus. Taken together, the system and methodas described herein increase the healthcare provider's ability to makebetter decisions about introphic, vasopressor and volume management inacutely ill patients than traditional methods.

In the foregoing specification, the invention has been described withreference to specific embodiments thereof. It will, however, be evidentthat various modifications and changes may be made thereto withoutdeparting from the broader spirit and scope of the invention. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. Throughout thisspecification, unless the context requires otherwise, the word“comprise” and its variations, such as “comprises” and “comprising,”will be understood to imply the inclusion of a stated item, element orstep or group of items, elements or steps but not the exclusion of anyother item, element or step or group of items, elements or steps.Furthermore, the indefinite article “a” or “an” is meant, to indicateone or more of the item, element or step modified by the article.

Having now fully set forth the preferred embodiments and certainmodifications of the concept underlying the present invention, variousother embodiments as well as certain variations and modifications of theembodiments herein shown and described will obviously occur to thoseskilled in the art upon becoming familiar with said underlying concept.It should be understood, therefore, that the invention may be practicedotherwise than as specifically set forth herein.

What is claimed is:
 1. A system for predicting cardiac stroke volumeresponsiveness in a patient, comprising: an ultrasound transducer; and acomputer processor in data communication with said ultrasoundtransducer, said computer processor having computer executable codestored thereon configured to: in response to receiving signals from saidultrasound transducer, determine that a change has occurred in apatient's physiology corresponding to at least one of a change of inflowinto the patient's right ventricle and a change of outflow from thepatient's left ventricle, wherein said computer executable code isfurther configured to make said determination that a change has occurredin a patient's physiology by determining an integral of flow velocitiesduring a time of flow through the patient's left ventricular outflowtract, and by determining a maximum and minimum diameter of thepatient's internal jugular vein resulting from respiratory variation inthe patient's internal jugular vein when positioned in an upright,seated position; receive a predetermined positive fluid bolusresponsiveness value range; determine whether said detected change iswithin said predetermined positive fluid bolus responsiveness valuerange; and in response to determining that said change is within saidpredetermined positive fluid bolus responsiveness value range, produce ahuman-readable output indicating that said patient has a likelihood ofpositive cardiac stroke volume response to a fluid bolus.
 2. The systemof claim 1, further comprising a mobile computing device in datacommunication with said computer processor, said mobile computing devicehaving computer executable code stored thereon configured to displaysaid human-readable output.
 3. A method for predicting cardiac strokevolume responsiveness in a patient, comprising: providing an ultrasoundtransducer; providing a computer processor in data communication withsaid ultrasound transducer; receiving at said processor signals fromsaid ultrasound transducer; in response to receiving said signals fromsaid ultrasound transducer, detecting at said computer processor achange in a patient's physiology corresponding to at least one of achange of inflow into the patient's right ventricle and a change ofoutflow from the patient's left ventricle, wherein said detecting achange in a patient's physiology further comprises determining anintegral of flow velocities during a time of flow through the patient'sleft ventricular outflow tract, and determining a maximum and minimumdiameter of the patient's internal jugular vein resulting fromrespiratory variation in the patient's internal jugular vein whenpositioned in an upright, seated position; determining at said computerprocessor whether said detected change is within a predeterminedpositive fluid bolus responsiveness value range; and in response todetermining that said change is within said predetermined positive fluidbolus responsiveness value range, producing at said computer processor ahuman-readable output indicating that said patient has a likelihood ofpositive cardiac stroke volume response to a fluid bolus administered tosaid patient.
 4. The method of claim 3, further comprising the steps of:providing a mobile computing device in data communication with saidcomputer processor; and displaying at said mobile computing device saidhuman-readable output.
 5. A method for administering a fluid bolus to apatient, comprising: providing an ultrasound transducer; providing acomputer processor in data communication with said ultrasoundtransducer; receiving at said processor signals from said ultrasoundtransducer; in response to receiving said signals from said ultrasoundtransducer, detecting at said computer processor a change in a patient'sphysiology corresponding to at least one of a change of inflow into thepatient's right ventricle and a change of outflow from the patient'sleft ventricle, wherein said detecting a change in a patient'sphysiology further comprises determining an integral of flow velocitiesduring a time of flow through the patient's left ventricular outflowtract, and determining a maximum and minimum diameter of the patient'sinternal jugular vein resulting from respiratory variation in thepatient's internal jugular vein when positioned in an upright, seatedposition; determining at said computer processor whether said detectedchange is within a predetermined positive fluid bolus responsivenessvalue range; in response to determining that said change is within saidpredetermined positive fluid bolus responsiveness value range,administering a fluid bolus to said patient.